A Belief Function Theory Method for Prognostics in Clogging Filters

Piero Baraldi (1) , Francesco Di Maio (1) , Francesca Mangili (1) , Enrico Zio (2)

1 Dipartimento di Energia [Milano]
2 SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec

This paper presents a similarity-based approach for the prediction of the Remaining Useful Life (RUL) of sea water filters placed upstream the heat exchangers of a nuclear reactor condenser. The prognostic approach is developed considering a library of reference degradation trajectories containing parameter observations taken from a set of similar equipments until their failures. The prediction of the RUL of the a filter is obtained by comparing its degradation trajectory to the reference trajectories and by properly aggregating the RULs of the training trajectories using a weighted sum which takes into account the similarity within test and training trajectories. In order to provide a measure of confidence in the RUL prediction in the form of a prediction interval, we place our work within the framework of belief function theory and we assign to each reference trajectory a belief proportional to its similarity to the test trajectory. A prediction interval is then obtained by properly combining these belief assignments using the Dempster's rule.

Domaines: Sciences de l'ingénieur [physics]

Piero Baraldi, Francesco Di Maio, Francesca Mangili, Enrico Zio. A Belief Function Theory Method for Prognostics in Clogging Filters. Chemical Engineering Transactions, 2013, 33, pp.847-852. ⟨10.3303/CET1333142⟩. ⟨hal-00926991⟩